Global Access
Experience Required: Intermediate
Appropriate for students with existing/moderate exposure to subject
Program Cost
Tuition: $3,180
Duration
2 Weeks
Location
New York, NY
Format
In-person
Cohort Size
Undisclosed
Eligibility
Rising Sophomores, Juniors, Seniors
Year Established
Undisclosed
Category
CS, Math, AI
The Machine Learning (ML) Summer Program at NYU Tandon School of Engineering is an intensive, two-week academic course for high school students focused on the foundational concepts and practical applications of modern artificial intelligence. Offered through NYU Tandon’s K–12 STEM Education programs, the program is held at NYU’s Washington Square Park campus and introduces students to core computational ideas including data modeling, algorithmic prediction, and model evaluation.
The curriculum is structured around full-day instruction that blends lectures with applied coding exercises. Students are introduced to essential techniques such as linear and logistic regression, classification, clustering, and neural networks. Daily work includes programming assignments and guided problem-solving using Python and real datasets. For 2026, the program is offered in three sessions: June 15–27, July 6–17, and July 20–31.
Admission is selective and requires the completion of Algebra 2 and basic computer programming experience. While historically a commuter-only program, for 2026, students (ages 15+) may choose an optional residential track, staying in NYU residence halls. The base tuition is $3,180, with additional weekly fees for those electing to live on campus. The application deadline for the 2026 cycle is May 15.
Institutionally, the program reflects the instructional frameworks used in Tandon’s undergraduate engineering curriculum. Students leave with concrete experience in computational thinking and algorithmic reasoning, making the program ideal for those seeking a rigorous introduction to machine learning as a technical engineering discipline.
The curriculum for NYU Tandon’s Machine Learning program is developed by Tandon engineering faculty and uses the same core conceptual frameworks taught in the school’s undergraduate artificial intelligence and data science courses.
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